Planning stability in a product recovery system

Recovery of used products is an issue of growing importance due to customer expectations and environmental regulation. As a consequence, companies need to adapt their material management taking into account inbound flows of used products. Corresponding inventory control models have been proposed in literature. In this paper we address the issue of planning stability in a product recovery context. To this end, we consider rolling horizon planning for a stock point facing stochastic demand and product returns. We analyze the impact of the return flow on planning stability and compare the system behaviour with a traditional production environment. We show that structural results derived for traditional inventory models remain valid in a product recovery context. Moreover we discuss counterintuitive effects resulting from interaction between planning stability and stock levels.     

Quantitative evaluation of product disassembly for recycling

This paper presents a method for evaluating the ease-of-disassembly of products. Its primary use is in designing products for recycling, but it also facilitates consideration of servicing and maintenance, and making environmentally-related decisions. The method is developed and discussed in the context of relatively small products that can be disassembled by a seated person using hand-held tools. The evaluation procedure is centered around a spreadsheet-like chart and uses a catalog of task difficulty scores. The scores were derived from work-measurement analyses of standard disassembly tasks, and provide a means of identifying weaknesses in the design and comparing alternatives quantitatively. The structure of the evaluation chart and the derivation of difficulty scores are explained, followed by a demonstration of analyzing a computer central processing unit. The limitations of the method and future extensions are outlined.     

Flexible disassembly planning considering product conditions

To increase the economic benefit of product recovery at the end of life of a consumer product, the profit margins should be augmented. This can be realised by utilising the existing flexibility of today’s mostly manually-conducted disassembly processes. Moreover, with increased economic benefits, the recovery becomes even more attractive, which is also beneficial to the environment. A key component of product recovery is disassembly. Allowing different disassembly states (or levels) per core (i.e. recovered product) increases flexibility in planning. This should result in higher profits, as long as the flexibility is still manageable for the companies. This study focuses on flexible disassembly planning, i.e. the integration of sequencing aspects into disassembly (process) planning. In addition, we further incorporate the condition of items in the core, item damaging, purity requirements, special treatment of hazardous items and several limitations like core availability, item, module and material distribution, disposal and labour time limit. We base our developed mixed integer linear programme on graphs, such as the disassembly state graph for sequencing, and a hypergraph to model the core condition. Lastly, our considerations are illustrated by a numerical example.     

Configuration analysis to support product redesign for end-of-life disassembly

End-of-life product disassembly is an important process that makes the parts of a product available for different material and part recycling processes at end of its useful life. However, the efficiency of the disassembly process greatly affects the economics of meeting the environmental goals set for the product. An important determinant of the efficiency of disassembly is the product configuration. Therefore, it is essential for the designer to assess these implications of the configuration while designing a product for end-of-life disassembly. In this paper, a formal model, called the Configuration-Value (CV) model, is proposed to evaluate and analyse the effect of configuration on disassembly. The model focuses on the rate of value extraction during the disassembly process. The model is used to identify the critical bottlenecks in the configuration, to help the designer to identify the design changes that need to be made to improve the product 'disassemblability'. An example is presented to demonstrate the application of the proposed model.     

An approach for estimating the end-of-life product disassembly effort and cost

Disassembly is the process of physically separating a product into its parts or subassembly pieces. The overall economics of the disassembly process, and in particular the cost to disassemble, is still not well understood. In this paper our goal is to introduce a methodology that will support and facilitate the economic analysis of the disassembly activity. We present a multi-factor model to compute the disassembly effort index (DEI) score, which is representative of the total operating cost to disassemble a product. The DEI score can then be compared against the projected market value of the disassembled parts and subassemblies to get an economic measure. To develop the DEI model we surveyed a variety of commercial disassembly facilities. Based on these surveys we propose a multifactor weighted estimation scheme. The seven factors are (i) time, (ii) tools, (iii) fixture, (iv) access, (v) instruct, (vi) hazard, and (vii) force requirements. The DEI scale is defined in the 0 to 100 range. This range is assigned on a weighted basis to each of the seven factors. For each factor, an independent utility scale is formulated, using the assigned range as anchors. Using a conversion scale the DEI score is used to derive an estimate of disassembly cost and the disassembly return on investment. An example is presented.     

Interactive AR-assisted product disassembly sequence planning (ARDIS)

This paper presents a proof-of-concept novel near real-time interactive AR-assisted product disassembly sequence planning system (ARDIS) based on product information, such as interference matrix and 3D models. The system is developed using Unity and consists of three modules, including an intelligent disassembly sequence planning module, an automatic content authoring module and an intuitive augmented reality (AR) user interface (UI) with various features, such as a virtual panel for customisation and an option panel for sequence regeneration. Given the retrieval targets specified by a user, optimised disassembly sequences are computed using an evolutionary computing algorithm. For the sequences computed, the respective AR disassembly instruction sequences, such as 2D text instructions and animated 3D models, are generated dynamically based on a taxonomy that links each disassembly step in a sequence with the corresponding Unity templates that have been created beforehand. Hence, the need for manual authoring to provide AR disassembly guidance is reduced. If necessary, the user can request for alternative disassembly sequences which can be re-computed in near real-time. Several case studies have been carried out to demonstrate and evaluate the performance of the system within the laboratory environment.     

Partial disassembly sequencing considering acquired end-of-life product age distributions

Uncertainty management is a priority in remanufacturing operations due to uncertain end-of-life (EoL) product quality, quantity and return timing. Ignoring EoL product uncertainty can result in inefficient remanufacturing operations. In this work, an approach is developed that addresses the impact of EoL product quality uncertainty on partial disassembly sequences. Disassembly is performed on nearly all EoL products, yet it is vulnerable to uncertain EoL product quality, defined in this work as the remaining value of an EoL product compared to original equipment manufacturer standards. The developed approach converges to an optimal or near-optimal partial disassembly sequence provided that information regarding acquired EoL product age distributions is known and correlates to EoL product quality. A mathematical framework is introduced to evaluate disassembly sequences based on profit standard deviation and profit probability as well as the traditionally used expected profit. The approach is tested on an example case study to investigate the impact of uncertain quality on the optimal or near-optimal disassembly sequence, expected profit, profit standard deviation and profit probability.     

Integrated approach for disassembly processes generation and recycling evaluation of an end-of-life product

An integrated approach for noble recycling is presented that puts forward the functional value of products and components. In a first step, the approach determines all feasible automatic disassembly sequences and in a second step all applicable recycling activities. This allows one to determine the most appropriate recycling process for an end-of-life product considering concurrent recycling techniques. The feasible automatic disassembly sequences are established by simulation in a virtual environment. The required generic disassembly product model, as well as the generic disassembly activity model, is presented by means of static and dynamic object-oriented diagrams. The recycling evaluation establishes an efficient solution responding to economic and ecological decision criteria. It is calculated applying a Goal-Programming approach transforming the multi-objective linear problem into a monocriteria linear program. The techno-economic decision model applied is Linear Activity Analysis. It allows one to integrate the generated disassembly processes based on single disassembly activities as well as other recycling techniques.     

A new model for estimating End-of-Life disassembly effort during early stages of product design

Clean Technologies and Environmental Policy - In this paper, a new model for estimating disassembly effort during early stages of product design is proposed. The model has been developed by...     

Digital tools for material selection in product design

The increasing number of normalized materials, promoters and users led to a significant amount and diversity of databases and software for material selection, presenting differentiating abilities for the materials selection process.     

Evaluation model and algorithm of product disassembly process with stochastic feature

Disassembly planning is considered as the optimization of disassembly sequences with the target of the shortest disassembly time, the lowest disassembly cost, and the minimum disassembly energy consumption. However, obsolete products suffer from the influence of a variety of uncertainties, the disassembly process of products has the strong uncertain feature. Traditionally, to account for this uncertainty, each removal operation or removal task is assumed to be an activity or event with certain probability, and the determination of the optimal path of a disassembly process is merely a probabilistic planning problem based on this assumption. In this article, based on the established stochastic disassembly network graph, combined with different disassembly decision-making criterion, typical stochastic models for disassembly time analysis are developed. In addition, a two-phase approach is proposed to solve the typical stochastic models. Initially, according to different removal probability density functions, disassembly probability density functions of feasible disassembly paths are determined by a time-domain method or frequency-domain method, and additionally, after the disassembly probability density functions have been obtained, the quantitative evaluation of a product disassembly process and stochastic optimization of feasible disassembly paths are realized by a numerical solution method. Finally, a numerical example is illustrated to test the proposed concepts and the effectiveness of the proposed approach.     

Disassembly line in product recovery

There are several situations in a product recovery environment where products may be disassembled for economical and regulatory reasons. The disassembly line is perhaps the most suitable setting for disassembly of large products (consisting of numerous components) as well as small products received in large quantities. This paper discusses the importance of a disassembly line in product recovery. The objective of the disassembly line is to utilize the available resources as efficiently as possible while meeting the demand for recovered parts. However, there are many complicating matters that need to be considered to create an efficient disassembly line. Our primary goal is to discuss these issues and provide a better understanding of the complications and their effects on the disassembly line. We also demonstrate how some important factors in disassembly can be accommodated to balance a paced disassembly line by modifying the existing concept of assembly line balancing. An example is presented to illustrate the approach.     

The value of information systems for product recovery management

This article sheds light on the role of information systems in product recovery management. We first develop analytical models and then provide a numerical example to determine under what conditions investments in Information-intensive Product Recovery Systems (IPRS) are economically justifiable for manufacturers and when policy-makers need to consider facilitating their implementation. The results of the analytical models indicate that the recovery network (collection) structure and product characteristics determine if precision improvements or increased sorting speed associated with IS investments will lead to higher profit gains. Manufacturers should carefully assess conflicting impacts of current manufacturing and recycling technology trends on the value of IPRS. Implementing IPRS might end up reducing manufacturers' profits under a highly time efficient decentralised collection structure. We show that negotiations with competitors about IPRS implementation may lead to a win–win situation and allow consumers to enjoy the lowest product price if the binding force of the agreement is strong. Otherwise, some manufacturers follow free-rider strategies. This article has immediate application to manufacturers' IS strategy and to government policy-makers considering investing in and/or structuring product recovery closed-loop supply chain processes within their jurisdictions. It also opens a potential stream of research concerning the role of IPRS to automate, informate and transform closed-loop supply chains for eco-efficiency.     

Analysis of a product recovery system

The continuous growth in consumer waste in recent years has seriously threatened the environment. Environmentally conscious manufacturing and product recovery has become an obligation to the environment and to society. Many countries are contemplating regulations that force manufacturers to take back used products from consumers so that the components and materials retrieved from the products may be reused and/or recycled. We focus on a product recovery system in a remanufacturing system. Product recovery aims to minimize the amount of waste sent to landfills by recovering materials and parts from old or outdated products by means of recycling and remanufacturing. It should be considered when designing and managing the manufacturing systems. We propose a new analytical approach to evaluating the product recovery system with stochastic variability. This model applies the traditional inventory theory to the production/inventory management with consideration for disposal and return. The system is formulated by a discrete time Markov chain. It is composed of the states denoted by the number of the inventory, the transition probabilities between states and the costs associated with the transitions. Using the Markov analysis, we can calculate the total expected average cost per period exactly. Numerical examples are given to show the property of the management system and optimize the product recovery system.     

Dynamic buy-back for product recovery in end-of-life spare parts procurement

The efficient supply of spare parts is of prime concern for original equipment manufacturers (OEM). While manufacturing the parent product, spare parts can be sourced efficiently by using existing manufacturing facilities. This situation completely changes once the original equipment manufacturer ceases production of the parent product. In addition to traditional spare parts sources in the form of final order and remanufacturing, the option to buy back parts or products provides a viable alternative in the end-of-life phase. This can prevent the OEM from fulfilling his spare parts availability obligation or increase his ability to remanufacture. Current practice in industry is, on the one hand, to offer trade-in campaigns to acquire functional products from customers by giving substantial discounts on a new-generation product. On the other hand, trade-in rebates are given when customers return their broken parts in exchange for spare parts. We propose the consideration of a third option, i.e. to buy back broken products in order to improve control of both demand for spare parts and supply of recoverable parts. This contribution seeks to assess the potential benefit of buy-back strategies in contrast to both traditional sourcing and trade-in campaigns for different settings regarding information availability and buy-back flexibility. For each situation, a MILP formulation is presented, and in a numerical study we analyse the circumstances under which the buy-back of broken products is especially beneficial for the OEM.     

Strategies for evaluating performance of flexibility in product recovery system

In view of the increasing business opportunities with changing customer attitudes and stricter legislations, the handling of returns has become a daunting challenge. The need for decision models for evaluating return performance has been observed in the academia and the corporate world. To improve return system performance, integrated flexible reverse enterprise systems have attracted attention from researchers as well as practitioners. This paper addresses these critical issues and proposes a novel integrated and Flexible recovery system decision model. The proposed model aims to facilitate enterprises in assessing their product recovery system capability, and in improving overall performance. The proposed model is a natural extension of several well-grounded policies for conventional reverse supply chains and can be verified on a simulation platform.     

A Petri Net based approach to determine the disassembly strategy of a product

In order to protect the environment and regain value added to products, a process known as disassembly has come into the limelight. This process is to be applied to reuse abandoned goods and materials. Manufacturers are being forced to establish disassembly plants and to develop their products' designs so as to maintain the government's dictate to dispose off their products in an environmentally responsible manner. This research presents a cost-based heuristic analysis for a circuit board assembly. Various components of the product and their assembly relationships are represented by a Petri Net diagram. Firing the transitions of the disassembly Petri Net is integrated with cost-based indices to develop an effective disassembly strategy. The methodology discussed here simplifies the decisionmaking process involved in disassembly planning. A comprehensive disassembly process planning system is proposed here and is exemplified by a case study of circuit board assembly.     

Analysis of flexible decision strategies for sustainability-focused green product recovery system

Identifying and analysing key decision variables that an organisation can opt for in order to initiate resource recovery from return activities and improve overall performance is a challenge. Therefore, to assist organisations which are involved in or about to initiate an effective recovery process, this paper provides guidelines to establish flexible decision strategies using the interpretive structural modelling (ISM) approach. This study has identified interrelationships between green variables such as supplier commitment, cost, regulations, etc. and has categorised relevant enablers. Further, variables such as capacity utilisation, customer satisfaction, energy consumption reduction, etc. are recognised as outcomes or results. After statistically verifying these variables, it has been inferred that driving enablers aid in promoting performance variables, while the result variables represent outcomes achieved via the driving variables. Further, using MICMAC analysis, a graphical categorisation of the variables is done on the basis of the impact on performance. Later prioritisation of variables having high driving power and low dependence is conducted. Inputs in the proposed model are taken through a case study conducted in the paper industry. The proposed model can be quite helpful and can act as a generic tool to achieve the desired performance improvement of green product recovery systems.     

An improved co-evolutionary algorithm for green manufacturing by integration of recovery option selection and disassembly planning for end-of-life products

There is a strong need for recovery decision-making for end-of-life (EOL) products to satisfy sustainable manufacturing requirements. This paper develops and tests a profit maximisation model by simultaneously integrating recovery option selection and disassembly planning. The proposed model considers the quality of EOL components. This paper utilises an integrated method of multi-target reverse recursion and partial topological sorting to generate a feasible EOL solution that also reduces the complexity of genetic constraints handling. In order to determine recovery options, disassembly level and disassembly sequence simultaneously, this paper develops an improved co-evolutionary algorithm (ICA) to search for an optimal EOL solution. The proposed algorithm adopts the evolutionary mechanism of localised interaction and endosymbiotic competition. Further, an advanced local search operator is introduced to improve convergence performance, and a global disturbance strategy is also suggested to prevent premature convergence. Finally, this paper conducts a series of computational experiments under various scenarios to validate the meta-heuristic integrated decision-making model proposed and the superiority of the developed ICA. The results show that the proposed approach offers a strong and flexible decision support tool for intelligent recovery management in a ubiquitous information environment. We discuss the theoretical and practical contributions of this paper and implications for future research.